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A comprehensive introduction to the foundations of model checking, a fully automated technique for finding flaws in hardware and software; with extensive examples and both practical and theoretical exercises.

We are all increasingly dependent on software systems to run the technology we use every day, so we need these systems to be both reliable and safe.This book presents papers from the NATO Advanced Study Institute Summer School Dependable Software Systems Engineering, held in Marktoberdorf, Germany, in July and August 2014. Lecturers were drawn from prestigious research groups representing both industry and academia, and the course was designed as an in-depth presentation and teaching of state-of-the-art scientific techniques and methods covering research and industrial practice as well as scientific principles.Topics covered

Spectroscopic methods ‐ of which nuclear magnetic resonance (NMR) is one of the most vital players ‐ have almost entirely replaced those old “wet chemistry”‐based approaches and the art has become a science. The fact that any automatic structure verification (ASV) system measures the degree of compatibility between a proposed molecular structure and the available spectroscopic data is of fundamental importance. This chapter presents a brief survey of existing computer‐based verification systems. It reviews the rudiments of NMR data acquisition and processing. The chapter also presents the well‐known theory on signal processing to lay the basis required to ensure a minimum level of data quality. It shows some practical examples as well as some general recommendations that could be followed in the conditions commonly used in the context of verification by NMR.

This article discusses the relationship between mathematical proof and the digital computer from the viewpoint of the 'sociology of proof': that is, an understanding of what kinds of procedures and arguments count for whom, under what circumstances, as proofs. After describing briefly the first instance of litigation focusing on the nature of mathematical proof, the article describes a variety of 'cultures of proving' that are distinguished by whether the proofs they conduct and prefer are (i) mechanized or non-mechanized and (ii) formal proofs or 'rigorous arguments'. Although these 'cultures' mostly coexist peacefully, the occasional attacks from within one on another are of interest in respect to what they reveal about presuppositions and preferences. A variety of factors underpinning the diverse cultures of proving are discussed.

Face and kinship verification using facial images is a novel and challenging problem in computer vision. In this paper, we propose a new system that uses discriminative information, which is based on the exponential discriminant analysis (DIEDA) combined with multiple scale descriptors. The histograms of different patches are concatenated to form a high dimensional feature vector, which represents a specific descriptor at a given scale. The projected histograms for each zone use the cosine similarity metric to reduce the feature vector dimensionality. Lastly, zone scores corresponding to various descriptors at different scales are fused and verified by using a classifier. This paper exploits discriminative side information for face and kinship verification in the wild (image pairs are from the same person or not). To tackle this problem, we take examples of the face samples with unlabeled kin relations from the labeled face in the wild dataset as the reference set. We create an optimized function by minimizing the interclass samples (with a kin relation) and maximizing the neighboring interclass samples (without a kinship relation) with the DIEDA approach. Experimental results on three publicly available face and kinship datasets show the superior performance of the proposed system over other state-of-the-art techniques.

Biometric systems are playing a key role in the multitude of applications and placed at the center of debate in the scientific research community. Among the numerous biometric systems, handwritten signature verification has got keen interest over the last three decades. Handwritten signature verification is the behavioral bio-metric system that discriminates the genuine signature from the pre-stored known signatures. It has been researched in the number of application areas like banking, financial and business transactions, cheque processing, access control and e-business etc. In this article, we surveyed the techniques of offline and online signature verification systems according to the taxonomy of classification model. A detailed background of signature verification system along with the available datasets are presented comprehensively. At the end, we presented the most notable challenges that guide the readers towards the current trends and future directions of the domain.

Identity protection is an indispensable feature of any information security system. An identity can exist in the form of digitally written signatures, biometric information, logos, etc. It serves the vital purpose of the owners’ verification and provides them with a safety net against their imposters, so its protection is essential. Numerous security mechanisms are being developed to achieve this goal, and information embedding is prominent among all. It consists of cryptography, steganography, and watermarking; collectively, they are known as data hiding (DH) techniques. In addition to providing insight into various DH techniques, this review prominently covers the image watermarking works that have positively influenced its relevant research area. To that end, one of the main aspects of this study is its inclusive nature in reviewing watermarking techniques, via which it aims to provide a 360 ∘ view of the watermarking technology. The main contributions of this study are summarised below. The proposed study covers more than 100 major watermarking works that have positively influenced the field and continue to do so. This approach makes the discussion effective as it allows us to pivot on the vital watermarking works that have positively influenced the research area instead of just highlighting as many existing methods as possible. Moreover, it also empowers us to provide the readers with an insight into the current research trends, the pros and cons of the state-of-the-art methods, and recommendations for future works. In addition to reviewing the state-of-the-art watermarking works, this study solves the issue of reverse-engineering the main existing watermarking methods. For instance, most recent surveys have focused primarily on reviewing as many watermarking works as possible without probing into the actual working of the techniques. This approach can leave the readership without a vital understanding of implementing or reverse-engineering a watermarking method. This issue is especially prevalent among newcomers to the watermarking field; hence, this study presents the breakdown of the well-known watermarking techniques. A new systematisation of classifying existing watermarking methods is proposed. It classifies watermarking techniques into two phases. The first phase divides watermarking methods into three categories based on the domain employed during watermark embedding. The methods are further classified based on other watermarking attributes in the following phase.